Learning to navigate using a lazy map

Abstract

In this paper we present a novel framework that allows a mobile robot to represent the environment and learn a task. The representation is a `lazy map' in which observation are stored. Reinforcement learning is used to enable a human teacher to train the robot using rewards and punishments.